Predictive geometallurgy: An interdisciplinary key challenge for mathematical geosciences
Predictive geometallurgy: An interdisciplinary key challenge for mathematical geosciences
van den Boogaart, K. G.; Tolosana-Delgado, R.
Abstract
Predictive geometallurgy tries to optimize the mineral value chain based on a precise and quantitative understanding of: the geology and mineralogy of the ores, the minerals processing, and the economics of mineral commodities. This chapter describes the state of the art and the mathematical building blocks of a possible solution to this problem. This solution heavily relies on all classical fields of mathematical geosciences and geoinformatics, but requires new mathematical and computational developments. Geometallurgy can thus become a new defining challenge for mathematical geosciences, in the same fashion as geostatistics has been in the first 50 years of the IAMG.
Keywords: Geostatistics; Statistical scales; Microstructure; Computational geometry; Processing optimisation; Value of information; Mineral liberation analyser; QUEMSCAN
-
Book chapter
Daya Sagar, B.S.; Cheng, Qiuming; Agterberg, Frits: Handbook of Mathematical Geosciences: Fifty Years of IAMG, Cham: Springer, 2018, 978-3-319-78998-9, 673-686
DOI: 10.1007/978-3-319-78999-6_33
Cited 18 times in Scopus
Permalink: https://www.hzdr.de/publications/Publ-28500